The goal of this project-based learning activity is “How to build a better catapult,” and using data analysis and linear regression can allow students to make interpretations based on the data collected. After experimenting with their catapults, students will further understand their results by creating displays and using linear regression to show the relationship between distance traveled and time in the air. Using linear regression, students can improve their results by making modifications to their catapults based on their interpretations. They can also use a trend line to make future predictions to analyze the relationship between distance and time. The scaffolding activity reinforces the mathematical and data analysis concepts needed to build the best catapult.
PROJECT DESIGN: STUDENT LEARNING GUIDE
Project: How to build a better catapult
Driving Question: How can we build the best catapult?
Final Product(s) Presentations, Performances, Products and/or Services
Learning Outcomes/Targets knowledge, understanding & success skills needed by students to successfully complete products
Checkpoints/Formative Assessments to check for learning and ensure students are on track
Instructional Strategies for All Learners provided by teacher, other staff, experts; includes scaffolds, materials, lessons aligned to learning outcomes and formative assessments
Group: Create a Scatter plot and find the trend line for Flight Times and Distance from NYC to other US cities Individual: Practice Worksheet on small sample data set
CC.2.2.HS.C.6 Interpret functions in terms of the situations they model.
CC.2.4.8.B.1 Analyze and/or interpret bivariate data displayed in multiple representations.
CC.2.4.HS.B.2 Summarize, represent, and interpret data on two categorical and quantitative variables.
CC.2.4.HS.B.3 Analyze linear models to make interpretations based on the data.
Observation and discussion will take place between myself and the students as they are working in small groups.
After completing the activity, a class discussion will allow for further discussion on uses of trend lines and linear regression in data analysis, and the interpretations that can be made based on the data.
An exit activity in the form of individual practice of a small sample data set will reinforce the concepts of the lesson.
Students will be given an introduction on how scatter plots and trend lines can be used to interpret and analyze data. Students, at this part of the school year, should have prior knowledge of linear equations, graphing, and methods to display data and statistics. Using a worksheet, the students will plot the data to determine the relationship between distance and flight time from New York City to other US cities. Once the data has been displayed, a trend line will be drawn to interpret and further analyze the data. The trend line will allow students to create a linear equation to describe the trend of the scatter plot and make interpretations based on the data. A class discussion will take place on how trend lines can be used to show correlation and analyze the results to show a linear relationship. The class will conclude with individual practice on a small sample set of data to reinforce the concepts of the learning activity.
PROJECT DESIGN: STUDENT LEARNING GUIDE
Presentations, Performances, Products and/or Services
knowledge, understanding & success skills needed by students to successfully complete products
to check for learning and ensure students are on track
provided by teacher, other staff, experts; includes scaffolds, materials, lessons aligned to learning outcomes and formative assessments
Create a Scatter plot and find the trend line for Flight Times and Distance from NYC to other US cities
Individual:
Practice Worksheet on small sample data set
situations they model.
CC.2.4.8.B.1 Analyze and/or interpret bivariate data displayed in multiple representations.
CC.2.4.HS.B.2 Summarize, represent, and interpret data on two categorical and quantitative variables.
CC.2.4.HS.B.3 Analyze linear models to make interpretations based on the data.
After completing the activity, a class discussion will allow for further discussion on uses of trend lines and linear regression in data analysis, and the interpretations that can be made based on the data.
An exit activity in the form of individual practice of a small sample data set will reinforce the concepts of the lesson.